Adaptive baseline fitting for 1H MR spectroscopy analysis. Issue 1 (14th August 2020)
- Record Type:
- Journal Article
- Title:
- Adaptive baseline fitting for 1H MR spectroscopy analysis. Issue 1 (14th August 2020)
- Main Title:
- Adaptive baseline fitting for 1H MR spectroscopy analysis
- Authors:
- Wilson, Martin
- Abstract:
- Abstract : Purpose: Accurate baseline modeling is essential for reliable MRS analysis and interpretation—particularly at short echo‐times, where enhanced metabolite information coincides with elevated baseline interference. The degree of baseline smoothness is a key analysis parameter for metabolite estimation, and in this study, a new method is presented to estimate its optimal value. Methods: An adaptive baseline fitting algorithm (ABfit) is described, incorporating a spline basis into a frequency‐domain analysis model, with a penalty parameter to enforce baseline smoothness. A series of candidate analyses are performed over a range of smoothness penalties, as part of a 4‐stage algorithm, and the Akaike information criterion is used to estimate the appropriate penalty. ABfit is applied to a set of simulated spectra with differing baseline features and experimentally acquired 2D MRSI—both at a field strength of 3 Tesla. Results: Simulated analyses demonstrate metabolite errors result from 2 main sources: bias from an inflexible baseline (underfitting) and increased variance from an overly flexible baseline (overfitting). In the case of an ideal flat baseline, ABfit is shown to correctly estimate a highly rigid baseline, and for more realistic spectra a reasonable compromise between bias and variance is found. Analysis of experimentally acquired data demonstrates good agreement with known correlations between metabolite ratios and the contributing volumes of gray and whiteAbstract : Purpose: Accurate baseline modeling is essential for reliable MRS analysis and interpretation—particularly at short echo‐times, where enhanced metabolite information coincides with elevated baseline interference. The degree of baseline smoothness is a key analysis parameter for metabolite estimation, and in this study, a new method is presented to estimate its optimal value. Methods: An adaptive baseline fitting algorithm (ABfit) is described, incorporating a spline basis into a frequency‐domain analysis model, with a penalty parameter to enforce baseline smoothness. A series of candidate analyses are performed over a range of smoothness penalties, as part of a 4‐stage algorithm, and the Akaike information criterion is used to estimate the appropriate penalty. ABfit is applied to a set of simulated spectra with differing baseline features and experimentally acquired 2D MRSI—both at a field strength of 3 Tesla. Results: Simulated analyses demonstrate metabolite errors result from 2 main sources: bias from an inflexible baseline (underfitting) and increased variance from an overly flexible baseline (overfitting). In the case of an ideal flat baseline, ABfit is shown to correctly estimate a highly rigid baseline, and for more realistic spectra a reasonable compromise between bias and variance is found. Analysis of experimentally acquired data demonstrates good agreement with known correlations between metabolite ratios and the contributing volumes of gray and white matter tissue. Conclusions: ABfit has been shown to perform accurate baseline estimation and is suitable for fully automated routine MRS analysis. Abstract : Click here for the video … (more)
- Is Part Of:
- Magnetic resonance in medicine. Volume 85:Issue 1(2021)
- Journal:
- Magnetic resonance in medicine
- Issue:
- Volume 85:Issue 1(2021)
- Issue Display:
- Volume 85, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 85
- Issue:
- 1
- Issue Sort Value:
- 2021-0085-0001-0000
- Page Start:
- 13
- Page End:
- 29
- Publication Date:
- 2020-08-14
- Subjects:
- ABfit -- automated -- MRSI -- open‐source -- spectral analysis -- spline
Nuclear magnetic resonance -- Periodicals
Electron paramagnetic resonance -- Periodicals
616.07548 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1522-2594 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/mrm.28385 ↗
- Languages:
- English
- ISSNs:
- 0740-3194
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5337.798000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16000.xml